In access control systems, statistical models are used to assess an individual's access patterns that describe access patterns related to individuals, groups of individuals, and/or locations, and possibly to detect unusual or anomalous behavior that may indicate a security threat. The reliability of a statistical model however depends on having an appreciable amount of data. This data is used to build the model. Therefore, building a statistical model of access patterns may result in unreliable models due to insufficient data. This will typically happen when a new user is introduced to the access control system, wherein during the first weeks or months after his/her introduction, there is not enough data available to build a model for this user.